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Electric power networks are among the world's most complex human-made systems. The developing smart grid is an inherently complex system which is rapidly evolving in both definition and implementation. Deployment of advanced technologies within the electric utility sector and usage of state-of-the-art computing systems provides companies with innovative capabilities to forecast electricity demand, influence customer usage patterns, create demand response program, optimize unit commitment, and prevent power outages. At the same time, these advances also lead to the generation of unprecedented data volumes, high data communications requirements, and increased system complexity. Utility companies must be capable of high-volume, high-speed data management and advanced analytics which are designed to transform data into actionable insights, if they strive to successfully implement a modern smart grid. As smart grid operations will leverage Advanced Metering Infrastructure (AMI) to drive more real time decision making and operational activities, complex event processing and stream computing are needed for the modern smart grid. This paper explores the challenges and benefits of transitioning to a smart grid, and explores new architectural approaches built on Lambda Architecture and other emerging software standards which may more effectively leverage established forms of complex event processing.
Liu et al. (Thu,) studied this question.
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